The Journal of Membrane Biology

, Volume 247, Issue 5, pp 395–408 | Cite as

Continuum Approaches to Understanding Ion and Peptide Interactions with the Membrane

  • Naomi R. Latorraca
  • Keith M. Callenberg
  • Jon P. Boyle
  • Michael Grabe
Article

Abstract

Experimental and computational studies have shown that cellular membranes deform to stabilize the inclusion of transmembrane (TM) proteins harboring charge. Recent analysis suggests that membrane bending helps to expose charged and polar residues to the aqueous environment and polar head groups. We previously used elasticity theory to identify membrane distortions that minimize the insertion of charged TM peptides into the membrane. Here, we extend our work by showing that it also provides a novel, computationally efficient method for exploring the energetics of ion and small peptide penetration into membranes. First, we show that the continuum method accurately reproduces energy profiles and membrane shapes generated from molecular simulations of bare ion permeation at a fraction of the computational cost. Next, we demonstrate that the dependence of the ion insertion energy on the membrane thickness arises primarily from the elastic properties of the membrane. Moreover, the continuum model readily provides a free energy decomposition into components not easily determined from molecular dynamics. Finally, we show that the energetics of membrane deformation strongly depend on membrane patch size both for ions and peptides. This dependence is particularly strong for peptides based on simulations of a known amphipathic, membrane binding peptide from the human pathogen Toxoplasma gondii. In total, we address shortcomings and advantages that arise from using a variety of computational methods in distinct biological contexts.

Keywords

Ion permeation Membrane elasticity Continuum Coarse grained Rhoptry protein 5 (ROP5) 

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Naomi R. Latorraca
    • 1
  • Keith M. Callenberg
    • 2
  • Jon P. Boyle
    • 1
  • Michael Grabe
    • 1
    • 3
    • 4
  1. 1.Department of Biological SciencesUniversity of PittsburghPittsburghUSA
  2. 2.Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational BiologyPittsburghUSA
  3. 3.Department of Computational & Systems BiologyUniversity of PittsburghPittsburghUSA
  4. 4.Department of Pharmaceutical Chemistry, Cardiovascular Research InstituteUniversity of California, San FranciscoSan FranciscoUSA

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